David S. Watson

48 papers A* 3A 5Journal 34Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Probably Approximately Correct Maximum A Posteriori Inference. CoRR Matthew Shorvon, Frederik Mallmann-Trenn, David S. Watson
2025	J	`jnl`	Autoencoding Random Forests. CoRR Binh Duc Vu, Jan Kapar, Marvin N. Wright, David S. Watson
2025	A	`conf`	BudgetIV: Optimal Partial Identification of Causal Effects with Mostly Invalid Instruments. AISTATS Jordan Penn, Lee M. Gunderson, Gecia Bravo Hermsdorff, Ricardo Silva, David S. Watson
2025	J	`jnl`	Competing narratives in AI ethics: a defense of sociotechnical pragmatism. AI Soc. David S. Watson, Jakob Mökander, Luciano Floridi
2025	J	`jnl`	Hierarchical Fuzzy Model-Agnostic Explanation: Framework, Algorithms, and Interface for XAI. IEEE Trans. Fuzzy Syst. Faliang Yin, Hak-Keung Lam, David S. Watson
2025	J	`jnl`	Missing value imputation with adversarial random forests - MissARF. CoRR Pegah Golchian, Jan Kapar, David S. Watson, Marvin N. Wright
2025	J	`jnl`	What Kind of Reasoning (if any) is an LLM actually doing? On the Stochastic Nature and Abductive Appearance of Large Language Models. CoRR Luciano Floridi, Jessica Morley, Claudio Novelli, David S. Watson
2024	J	`jnl`	A Genealogical Approach to Algorithmic Bias. Minds Mach. Marta Ziosi, David S. Watson, Luciano Floridi
2024	J	`jnl`	Bounding Causal Effects with Leaky Instruments. CoRR David S. Watson, Jordan Penn, Lee M. Gunderson, Gecia Bravo Hermsdorff, Afsaneh Mastouri, Ricardo Silva
2024	A	`conf`	Bounding causal effects with leaky instruments. UAI David S. Watson, Jordan Penn, Lee M. Gunderson, Gecia Bravo Hermsdorff, Afsaneh Mastouri, Ricardo Silva
2024	J	`jnl`	The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems. CoRR Jakob Mökander, Margi Sheth, David S. Watson, Luciano Floridi
2024	J	`jnl`	The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: What can they learn from each other? CoRR Jakob Mökander, Prathm Juneja, David S. Watson, Luciano Floridi
2023	A	`conf`	Adversarial Random Forests for Density Estimation and Generative Modeling. AISTATS David S. Watson, Kristin Blesch, Jan Kapar, Marvin N. Wright
2023	J	`jnl`	Correction to: The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems. Minds Mach. Jakob Mökander, Margi Sheth, David S. Watson, Luciano Floridi
2023	A*	`conf`	Explaining Predictive Uncertainty with Information Theoretic Shapley Values. NeurIPS David S. Watson, Joshua O'Hara, Niek Tax, Richard Mudd, Ido Guy
2023	J	`jnl`	Explaining Predictive Uncertainty with Information Theoretic Shapley Values. CoRR David S. Watson, Joshua O'Hara, Niek Tax, Richard Mudd, Ido Guy
2023	A*	`conf`	Intervention Generalization: A View from Factor Graph Models. NeurIPS Gecia Bravo Hermsdorff, David S. Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva
2023	J	`jnl`	Intervention Generalization: A View from Factor Graph Models. CoRR Gecia Bravo Hermsdorff, David S. Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva
2023	—	`conf`	Stochastic Causal Programming for Bounding Treatment Effects. CLeaR Kirtan Padh, Jakob Zeitler, David S. Watson, Matt J. Kusner, Ricardo Silva, Niki Kilbertus
2023	J	`jnl`	The Ethics of Online Controlled Experiments (A/B Testing). Minds Mach. Andrea Polonioli, Riccardo Ghioni, Ciro Greco, Prathm Juneja, Jacopo Tagliabue, David S. Watson, Luciano Floridi
2023	J	`jnl`	The Switch, the Ladder, and the Matrix: Models for Classifying AI Systems. Minds Mach. Jakob Mökander, Margi Sheth, David S. Watson, Luciano Floridi
2023	—	`conf`	Unfooling SHAP and SAGE: Knockoff Imputation for Shapley Values. xAI (1) Kristin Blesch, Marvin N. Wright, David S. Watson
2022	A	`conf`	Causal discovery under a confounder blanket. UAI David S. Watson, Ricardo Silva
2022	J	`jnl`	Causal discovery under a confounder blanket. CoRR David S. Watson, Ricardo Silva
2022	J	`jnl`	Conditional Feature Importance for Mixed Data. CoRR Kristin Blesch, David S. Watson, Marvin N. Wright
2022	J	`jnl`	Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice. Minds Mach. David S. Watson, Limor Gultchin, Ankur Taly, Luciano Floridi
2022	—	`conf`	Models for Classifying AI Systems: the Switch, the Ladder, and the Matrix. FAccT Jakob Mökander, Margi Sheth, David S. Watson, Luciano Floridi
2022	—	`conf`	Rational Shapley Values. FAccT David S. Watson
2022	J	`jnl`	Smooth densities and generative modeling with unsupervised random forests. CoRR David S. Watson, Kristin Blesch, Jan Kapar, Marvin N. Wright
2022	J	`jnl`	Stochastic Causal Programming for Bounding Treatment Effects. CoRR Kirtan Padh, Jakob Zeitler, David S. Watson, Matt J. Kusner, Ricardo Silva, Niki Kilbertus
2022	J	`jnl`	The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: what can they learn from each other? Minds Mach. Jakob Mökander, Prathm Juneja, David S. Watson, Luciano Floridi
2021	—	`—`	Explaining black box algorithms: epistemological challenges and machine learning solutions. David S. Watson
2021	J	`jnl`	Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice. CoRR David S. Watson, Limor Gultchin, Ankur Taly, Luciano Floridi
2021	A	`conf`	Local explanations via necessity and sufficiency: unifying theory and practice. UAI David S. Watson, Limor Gultchin, Ankur Taly, Luciano Floridi
2021	A*	`conf`	Operationalizing Complex Causes: A Pragmatic View of Mediation. ICML Limor Gultchin, David S. Watson, Matt J. Kusner, Ricardo Silva
2021	J	`jnl`	Operationalizing Complex Causes: A Pragmatic View of Mediation. CoRR Limor Gultchin, David S. Watson, Matt J. Kusner, Ricardo Silva
2021	J	`jnl`	Rational Shapley Values. CoRR David S. Watson
2021	J	`jnl`	Testing conditional independence in supervised learning algorithms. Mach. Learn. David S. Watson, Marvin N. Wright
2021	J	`jnl`	The explanation game: a formal framework for interpretable machine learning. Synth. David S. Watson, Luciano Floridi
2020	—	`conf`	Causal Feature Learning for Utility-Maximizing Agents. PGM David Kinney, David S. Watson
2020	J	`jnl`	Causal Feature Learning for Utility-Maximizing Agents. CoRR David Kinney, David S. Watson
2020	J	`jnl`	Spectrum: fast density-aware spectral clustering for single and multi-omic data. Bioinform. Christopher R. John, David S. Watson, Michael R. Barnes, Costantino Pitzalis, Myles J. Lewis
2019	J	`jnl`	Are the dead taking over Facebook? A Big Data approach to the future of death online. Big Data Soc. Carl Öhman, David S. Watson
2019	J	`jnl`	Testing Conditional Predictive Independence in Supervised Learning Algorithms. CoRR David S. Watson, Marvin N. Wright
2019	J	`jnl`	The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence. Minds Mach. David S. Watson
2018	J	`jnl`	Are the Dead Taking Over Facebook: A Big Data Approach to the Future of Death Online. CoRR Carl Öhman, David S. Watson
2018	J	`jnl`	Crowdsourced science: sociotechnical epistemology in the e-research paradigm. Synth. David S. Watson, Luciano Floridi
2016	J	`jnl`	Crowdsourced science: sociotechnical epistemology in the e-research paradigm. CoRR David S. Watson, Luciano Floridi